跳白块法内核 job4为主函数，这个我找了好久 那里都没有的

RGB与YUV格式的互相转换, 支持YUV420、YUV444、YUV4-RGB and YUV format conversion with each other to support the YUV420, YUV444, YUV422

很好的图象缩放代码,不会有矩尺,可以移植到任何平台-Very good image scaling code, will not have moments feet, you can migrate to any platform

CRF（条件随机场）的程序包，用于图像分析（恢复，分割），对图像进行建模-CRF (with the conditions of the airport) package for image analysis (restoration, segmentation), the image modeling

30个图像处理的VC++ 源代码，包括256色转灰度图,Hough变换,image_j1,PCA,Walsh变换,对比度拉伸,二值化变换,反色, 方块编码,傅立叶变换,高斯平滑,灰度均衡,均值滤波,拉普拉斯锐化（边缘检测）, 离散余弦变换,亮度增减,逆滤波处理,取对数,取指数,梯度锐化,图象处理,图像镜像, 图像平移,图像缩放,图像细化,图像旋转,维纳滤波处理,用Canny算子提取边缘,阈值变换,直方图均衡.-30 image processing VC++ Source code, including 256 colors to grayscale, Hough transform, image_j1, PCA, Walsh transform, contrast stretching, binarization transformation, anti-color, box encoding, Fourier Transform , Gaussian smoothing, gray balance, mean filter, Laplacian sharpening (edge detection), discrete cosine transform, the brightness increases and decreases in inverse filtering deal, check on the number of check index, the gradient sharpening, image processing, mirror image, image translation, image scaling, image thinning, image rotation, Wiener filtering treatment using Canny edge extraction operator, threshold transform, histogram equalization.

jpg与bmp的转换，在VC下可以直接运行 -jpg tran bmp, or bmp tran jpg

JPEG压缩编码系统源代码，用于学习制作图像处理的方法-JPEG compression coding system source code, used to learn how to make image processing method

一、本程序是《C/C++图像处理编程》出版一年多来修改、改进的结果。 程序有所修改，内容也有很大的增加。 二、书中演示程序的内容与DosImage程序相一致。DosImageN程序有较多 修改，有改正错误的，有提高性能的，难以一一列出。 -First, the procedure is

本程序为BP算法在一个简单分类中的应用,主要针对异或问题,有助于对本算法的理解

两个图像质量评价函数，psnr峰值信噪比，正则均方误差nmse，能可用于去噪图像和压缩图像的质量评价，很有用啊。-Two image quality evaluation of the function. Including psnr PSNR, it is mean-square error nmse other. Images can be used for de-noising and compression of image quality evaluation.

aniso - Anisotropic diffusion, following the robust statistics formulation. Examples of how to run this function are included at the end of aniso.m-aniso- Anisotropic diffusion, following the robust statistics formulation. Examples of how to run this function are included at the end of aniso.m